The artificial intelligence industry has reached a critical infrastructure pivot as 2026 marks the year that light-based interconnects officially take the throne from traditional electrical wiring. According to a landmark report from Nomura, the market for 1.6T optical modules is experiencing an unprecedented "supercycle," with shipments expected to explode from 2.5 million units last year to a staggering 20 million units in 2026. This massive volume surge is being accompanied by a fundamental shift in how chips communicate, as Silicon Photonics (SiPh) penetration is projected to hit between 50% and 70% in the high-end 1.6T segment.
This transition is not merely a speed upgrade; it is a survival necessity for the world's most advanced AI "gigascale" factories. As NVIDIA (NASDAQ: NVDA) and Broadcom (NASDAQ: AVGO) race to deploy the next generation of 102.4T switching fabrics, the limitations of traditional pluggable copper and electrical interconnects have become a "power wall" that only photonics can scale. By integrating optical engines directly onto the processor package—a process known as Co-Packaged Optics (CPO)—the industry is slashing power consumption and latency at a moment when data center energy demands have become a global economic concern.
Breaking the 1.6T Barrier: The Shift to Silicon Photonics and CPO
The technical backbone of this 2026 surge is the 1.6T optical module, a breakthrough that doubles the bandwidth of the previous 800G standard while significantly improving efficiency. Traditional optical modules relied heavily on Indium Phosphide (InP) or Vertical-Cavity Surface-Emitting Lasers (VCSELs). However, as we move into 2026, Silicon Photonics has become the dominant architecture. By leveraging mature CMOS manufacturing processes—the same used to build microchips—SiPh allows for the integration of complex optical functions onto a single silicon die. This reduces manufacturing costs and improves reliability, enabling the 50-70% market penetration rate forecasted by Nomura.
Beyond simple modules, the industry is witnessing the commercial debut of Co-Packaged Optics (CPO). Unlike traditional pluggable optics that sit at the edge of a switch or server, CPO places the optical engines in the same package as the ASIC or GPU. This drastically shortens the electrical path that signals must travel. In traditional layouts, electrical path loss can reach 20–25 dB; with CPO, that loss is reduced to approximately 4 dB. This efficiency gain allows for higher signal integrity and, crucially, a reduction in the power required to drive data across the network.
Initial reactions from the AI research community and networking architects have been overwhelmingly positive, particularly regarding the ability to maintain signal stability at 200G SerDes (Serializer/Deserializer) speeds. Analysts note that without the transition to SiPh and CPO, the thermal management of 1.6T systems would have been nearly impossible under current air-cooled or even early liquid-cooled standards.
The Titans of Throughput: Broadcom and NVIDIA Lead the Charge
The primary catalysts for this optical revolution are the latest platforms from Broadcom and NVIDIA. Broadcom (NASDAQ: AVGO) has solidified its leadership in the Ethernet space with the volume shipping of its Tomahawk 6 (TH6) switch, also known as the "Davisson" platform. The TH6 is the world’s first single-chip 102.4 Tbps Ethernet switch, incorporating sixteen 6.4T optical engines directly on the package. By moving the optics closer to the "brain" of the switch, Broadcom has managed to maintain an open ecosystem, partnering with box builders like Celestica (NYSE: CLS) and Accton to deliver standardized CPO solutions to hyperscalers.
NVIDIA (NASDAQ: NVDA), meanwhile, is leveraging CPO to redefine its "scale-up" architecture—the high-speed fabric that connects thousands of GPUs into a single massive supercomputer. The newly unveiled Quantum-X800 CPO InfiniBand platform delivers a total capacity of 115.2 Tbps. By utilizing four 28.8T switch ASICs surrounded by optical engines, NVIDIA has slashed per-port power consumption from 30W in traditional pluggable setups to just 9W. This shift is integral to NVIDIA’s Rubin GPU architecture, launching in the second half of 2026, which relies on the ConnectX-9 SuperNIC to achieve 1.6 Tbps scale-out speeds.
The supply chain is also undergoing a massive realignment. Manufacturers like InnoLight (SZSE: 300308) and Taiwan Semiconductor Manufacturing Company (NYSE: TSM) are seeing record demand for optical engines and specialized packaging services. The move toward CPO effectively shifts the value chain, as the distinction between a "chip company" and an "optical company" blurs, giving an edge to those who control the integration and packaging processes.
Scaling the Power Wall: Why Optics Matter for the Global AI Landscape
The surge in SiPh and CPO is more than a technical milestone; it is a response to the "power wall" that threatened to stall AI progress in 2025. As AI models have grown in size, the energy required to move data between GPUs has begun to rival the energy required for the actual computation. In 2026, data centers are increasingly mandated to meet strict efficiency targets, making the roughly 70% power reduction offered by CPO a critical business advantage rather than a luxury.
This shift also marks a move toward "liquid-cooled everything." The extreme power density of CPO-based switches like the Quantum-X800 and Broadcom’s Tomahawk 6 makes traditional fan cooling obsolete. This has spurred a secondary boom in liquid-cooling infrastructure, further differentiating the modern "AI Factory" from the traditional data centers of the early 2020s.
Furthermore, the 2026 transition to 1.6T and SiPh is being compared to the transition from copper to fiber in telecommunications decades ago. However, the stakes are higher. The competitive advantage of major AI labs now depends on "networking-to-compute" ratios. If a lab cannot move data fast enough across its cluster, its multi-billion dollar GPU investment sits idle. Consequently, the adoption of CPO has become a strategic imperative for any firm aiming for Tier-1 AI status.
The Road to 3.2T and Beyond: What Lies Ahead
Looking past 2026, the roadmap for optical interconnects points toward even deeper integration. Experts predict that by 2028, we will see the emergence of 3.2T optical modules and the eventual integration of "optical I/O" directly into the GPU die itself, rather than just in the same package. This would effectively eliminate the distinction between electrical and optical signals within the server rack, moving toward a "fully photonic" data center architecture.
However, challenges remain. Despite the surge in capacity, the market still faces a 5-15% supply deficit in high-end optical components like CW (Continuous Wave) lasers. The complexity of repairing a CPO-enabled switch—where a failure in an optical engine might require replacing the entire $100,000+ switch ASIC—remains a concern for data center operators. Industry standards groups are currently working on "pluggable" light sources to mitigate this risk, allowing the lasers to be replaced while keeping the silicon photonics engines intact.
In the long term, the success of SiPh and CPO in the data center is expected to trickle down into other sectors. We are already seeing early research into using Silicon Photonics for low-latency communications in autonomous vehicles and high-frequency trading platforms, where the microsecond advantages of light over electricity are highly prized.
Conclusion: A New Era of AI Connectivity
The 2026 surge in Silicon Photonics and Co-Packaged Optics represents a watershed moment in the history of computing. With Nomura’s forecast of 20 million 1.6T units and SiPh penetration reaching up to 70%, the "optical supercycle" is no longer a prediction—it is a reality. The move to light-based interconnects, led by the engineering marvels of Broadcom and NVIDIA, has successfully pushed back the power wall and enabled the continued scaling of artificial intelligence.
As we move through the first quarter of 2026, the industry must watch for the successful deployment of NVIDIA’s Rubin platform and the wider adoption of 102.4T Ethernet switches. These technologies will determine which hyperscalers can operate at the lowest cost-per-token and highest energy efficiency. The optical revolution is here, and it is moving at the speed of light.
This content is intended for informational purposes only and represents analysis of current AI developments.
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